Enterprise Modelling Building a Product Lifecycle (PLM)

Home , Materials management, Product lifecycle

Research in Interactive Design , Springer Verlag, 2009, vol. 3.

Enterprise Modelling: Building a Product Lifecycle (PLM) Model as a component of the integrated vision of the enterprise

Abir FATHALLAH 1, Julie Stal Le Cardinal 1, Jean Louis Ermine 2, Jean- Claude Bocquet 1

(1) : Industrial Engineering Laboratory, (2) : CEMANTIC Laboratory, Institue Telecom, Ecole Centrale Paris TELECOM & Management SudParis Grande Voie des Vignes 9, rue Charles Fourier - 91011, Evry Cedex - 92 295 Châtenay- Malabry CEDEX FRANCE FRANCE Phone : 33.(0)1.41.13.10.00 Phone: 33.(0)1.60.76.43.04 Fax : 33 (0)1.41.13.10.10 E-mail : [email protected] E-mail : [email protected]

Abstract: Enterprise modelling has proved to be an efficient rather then something occasionally forced onto the tool to study organisations‘ structure and facilitate decision enterprise. This reactivity necessitates the identification of making. The enterprise is a complex system that is required to the core enterprise processes and the development of a use its processes to generate value in a given environment discipline that organises all knowledge that is needed to (concurrent, market, suppliers and humanity). We focus on identify the need for change in enterprises and to carry out three management disciplines: Product Lifecycle Management that change expediently and professionally. In this paper we (PLM), Supply Chain Management (SCM) and Customer are interested in three core business processes, Product Relationship Management (CRM). These business processes Lifecycle Management (PLM), Supply Chain Management are so intertwined that the enterprise has to concentrate on the (SCM) and Customer Relationship Management (CRM). three to attain its economic objectives. To enhance the Those three activities are so intertwined that the company development of PLM, SCM and CRM models, the enterprise has ideally to work on managing its supply chain, its product needs to capitalise the knowledge necessary to adapt and apply lifecycle organisation and its customers‘ relations in order modelling techniques. Knowledge Management (KM) is a key attain its economic objectives, evolve in the global market factor to give a unified enterprise vision. Firstly, we propose an and assure its permanence in the socio- technical integrated enterprise model depicting the interactions between environment. Besides Knowledge Management (KM) could PLM, SCM, CRM and KM models. But a state of the art be a determinant factor to integrate enterprise key process showed that PLM models are scarce. Most of the PLM models and enhance their use. found depends strongly on the particular case studied and can We focus on three management disciplines, the Supply not be used with other enterprises. After defining the most Chain, the Customer Relationship and the Product Lifecycle. important components of the PLM vision, we propose to Besides we try to show the role of Knowledge management. organise these components into a formalised way. The study of If the supply chain, the product lifecycle and the customer SCM and CRM models proved to be helpful to structure these are proved to be key success factors in the enterprise, recent components. Finally the validation methodology that is to be studies (1990) are the role of Knowledge Management is established in our coming research works is not only to be used enterprise systems. with the PLM model presented in this paper but with SCM and In the first part of this article, we give an overview of CRM models also. enterprise modelling practices. Then we present, in the second part, our vision of enterprise systems and the Key words : Enterprise Modelling, Enterprise Systems, interaction between four key management functions: Product Product Lifecycle Management (PLM), Lifecycle Management (PLM), Customer relationship Management (CRM) and Supply Chain Management (SCM) as well as the position of Knowledge Management. 1- Introduction: The third part of the article is focusing on PLM models. In Enterprises, today, are facing a rapidly changing environment; the literature, there is scarce PLM modelling attempts, so we they can no longer make predictable long term provisions. To are proposing a model to illustrate the PLM vision with a adapt to this change enterprises need to evolve and be reactive semi- formal language (combining pictograms and formal so that change and adaptation should be a natural dynamic state

Paper Number -1- Copyright of IDMME - Virtual Concept

language). The steps that led to building this model are The most important research results and some of the explained too. reference papers investigating could be seen in Table1. We And finally, we expose the future research work that is based are trying, also, to have them organised into: functional on model validation. based approaches, data/information based approaches and resource based approaches. Vernadat adopted a similar 2- State of the art in Enterprise Modelling: classification in his books [Vernadat 1996, Vernadat 1999].

During the last decades, enterprise modelling has proven to be

a fertile research field. Numerous modelling approaches were

settled down and proved their effectiveness when modelling

the enterprise processes, information system, resources or

organisation: SADT, SASS, The IDEF family of languages

(IDEF0, IDEFx1, IDEF3..), CIMOSA, GRAI TOOLS, PERA,

GERAM, ARIS…These previous enterprise modelling

methodologies aims to provide a better understanding and a

uniform representation of the enterprise, support for designing

new parts of the enterprise and a control and monitoring

enterprise operations [Vernadat,1996].

Approach Modeling Method Main references Function IDEF0 (Integrated Computer- The IDEF family of languages. Aided Manufacturing Definition) Christopher Menzel & Richard J Mayer. University of Texas, www.idef.com Function SADT Structured Analysis and D.T. Ross, "Structured Analysis (SA): A Design Technique Language for Communicating Ideas," IEEE Transactions on Software Engineering , vol. 3, no. 1, pp. 16-34, Jan/Feb, 1977 Function IDEF3 The IDEF family of languages. Christopher Menzel & Richard J Mayer. University of Texas, www.idef.com Function IDEFx1 The IDEF family of languages. Data/Information Christopher Menzel & Richard J Mayer. University of Texas, www.idef.com Function SASS ( Structured Analysis and T De Marco. Structured analysis and System Specification ) system specification. ACM Classic Books Series Classics in software engineering 1979

Function CIMOSA CIM Open System - ESPRIT-AMICE. CIM-OSA - A Vendor Data/Information Architecture Independent CIM Architecture. Resources Proceedings of CINCOM 90, pages 177- 196. National Institute for Standards and Technology, 1990. -CIMOSA: enterprise engineering and integration, K. Kosanke a, F. Vernadat, M. Zelm, Computers in Industry 40 1999.83œ 97 Function GRAI G. Doumeingts, B. Vallespir, D. Chen, Data/Information GRAI grid, decisional modelling, in: P. Resources Bernus, K. Mertins, G. Schmith (Eds.), Handbook on Architecture of Information System International Handbook on Information Systems, Springer, Berlin, 1998. Function (Process) GERAM GERAM: Generalised Entreprise Data/Information Reference Architecture and Methodology. Resources IIT Force 1999 Table 1 : Main Enterprise Modelling techniques

Paper Number -2- Copyright IDMME - Virtual Concept

The development of enterprise modelling solutions, though, was mainly based on the identification of core business processes and the way they are used in day-to-day operations 3.1 œ Definition of Product Lifecycle Management to assume the enterprise functions. We will represent next the (PLM): four enterprise core businesses we are focusing on in this

research: Product Relationship Management (PLM), Supply The past three decades have seen phenomenal growth in

Chain Management (SCM), Customer Relationship investments in the area of product lifecycle management

Management (CRM) and Knowledge Management (KM). The (PLM) as companies exploit opportunities in streamlining

interactions studied between the models used to insure SCM, product lifecycle processes, and fully harnessing their data CRM, PLM or KM can help the enterprise‘s management assets. These processes span all product lifecycle phases

choose the suitable strategy and enhance the application of the from requirements definition, systems design/ analysis, and

chosen model in practice. simulation, detailed design, manufacturing planning, Combining the study of PLM, SCM and CRM allows a production planning, quality management, customer support,

covering of all enterprise‘s aspects: the Functional part, the in-service management, and end-of-life recycling. [PTC, Data/information part and the Resources part. PLM is an Needham, MA]. Information/Data//Functional approach. It is based on PLM systems will support business partners across the functional interoperability between the enterprise departments supply chain with needed product information and more and keeping traceability in product data during the lifecycle process integration (Supply Chain Management). [Terzi, 2005]. SCM is mainly a Functional approach, it is Furthermore PLM systems will support feedback of customer based on detailing (creating, sourcing, making processes and information into earlier product lifecycle phases to improve logistics functions) supply chain functions to facilitate their product quality (Customer Relationship Management). coordination and improve the performance of the entire supply [Abramovici et al, 2002] chain [Li et al, 2005]. CRM and KM are to be considered as 3.2 œ Definition of Supply Chain Management Information/Data//Resources approach. CRM needs collecting (SCM): customer‘ data which are implemented on different The Supply Chain is the set of procedures and software using Information systems. KM aims at a better use of enterprise for managing optimally the information flows, material flows resources via Knowledge and allows the capturing, and the interfaces between the different actors: suppliers, externalisation, formalisation and structuring of knowledge producers and customers that are related to the about enterprise processes [Kalpic & Bernus, 2002] manufacturing of a product or the delivery of a service. All the data concerning from the customer requirement until the distribution scheme, through the conception and production 3- An integrated Enterprise Model: data are gathered and used to build the supply chain In this research we consider an enterprise —made of a large [Eymery, 2003]. collection of concurrent business processes executed by a set Supply Chain Management, though, consists of monitoring, of functional entities (or resources) that contribute to business supervising and integrating all key business activities from objectives“ [Vernadat, 1996]. Managers need efficient tools for the final customer down to the raw materials suppliers process modelling and integration [Vernadat, ] to give them [Global Supply Chain Forum (GCCF): ou connue avent pour guidelines to conduct organization improvements [Melan, le —Research Roundtable of the International Center for 1993]. We are proposing to study the most important of these Competitive Excellence, de l‘Université de la Floride du enterprise process models in order to enhance their application, nord]: customer relationship management, customer services so following the classification of Shrivastava et al (1999), we management, demand management, order fulfilment, are interested in three core business processes: Supply Chain manufacturing flow management, procurement, product Management (SCM), Product Lifecycle Management (PLM) development and commercialization and returns [Lambert et and Customer Relationship Management (CRM). al, 2000]. The paper of Shrivastava et al (1999) is focusing on Supply Chain Management (SCM), Product Data Management (the 3.3 œ Definition of Customer Relationship Product Data Management discipline has evolved to PLM Management (CRM): since that) and Customer Relationship Management (CRM); it depicts the interactions between these business processes. This Acquiring, retaining, and partnering with selective customers to create superior value for the company and the customer is interaction is meant as follow: improving the enterprise efficiency with managing its Supply Chain, its Customers or its the main objective of Customer Relationship Management [Parvatiyar& Sheth, 2001]. Customer Relationship, in fact, is Product is almost related to working on the other enterprise factors. the —process that involves the development and leveraging of This vision is confirmed by Hervé Rolland, Vice president of market intelligence for the purpose of building and maintaining a profit-maximizing portfolio of customer sales development of IBM who considers that the PLM and CRM are the enterprise front office and the SCM and ERP are relationships“ [Zablah, et al 2004]. CRM allows companies the enterprise back office. [Debeacker, 2002]. to gather customer data swiftly, identify the most valuable customers over time, and increase customer loyalty by We will begin by a brief definition of those three enterprise management disciplines, and then we will explain the providing customized products and services [Rigby et al., 2002]. interactions between them .

Paper Number -3- Copyright IDMME - Virtual Concept

3.4 œ The Enterprise Integrated Model: The term —Knowledge Management“ is more than twenty SCM, PLM and CRM models are important success factors for years old. Karl Wiig, management consultant, coined it at a an enterprise. Those three activities are so intertwined that the 1986 Swiss conference sponsored by the United Nations company has ideally to work on managing its supply chain, its [Liebowitz, 1999]. One of the definition on KM is that it product lifecycle organisation and its customers‘ relations in —involves the identification and analysis of available and order attain its economic objectives, evolve in the global required knowledge, and the subsequent planning and control market and assure its permanence in the socio- technical of actions to develop knowledge assets so as to fulfil environment. But, we are adding a forth factor that we consider organisational objectives“.[Ann Macintosh, Artificial part of the important resources of an enterprise or an Intelligence Applications Institute, University of Edinburgh]. organisation: Knowledge. Besides the three success factors: the supply chain, the In fact, knowledge is an economic capital and a strategic product and the customer, the question of knowledge resource in the enterprise, it provides a competitive advantage handling emerged in the literature as a discipline that can and insures a stability for the company as it deals with the help the enterprise achieve their economic goals and preserve strategies, the organisational structure, the whole set of their —know how“ inside the company despite the renewal of processes, the human resources, communication and workers. information technologies. [Boughzala & Ermine, 2002].

Make To Stock

Supply Chain Strong interaction

Management confirmed by research papers.

Relationship needing

further investigation

Synchronising: Synchronising:

Design Chain & Supply Demand Chain & Supply

Chain Chain

Knowledge management

Customer Product Life cycle Relationship Management Management Synchronising: Build To Order Design Chain & Configuration To Order Demand Chain

Figure 1 : An integrated Enterprise Model: Interactions between PLM, SCM, CRM and KM models

Paper Number -4- Copyright IDMME - Virtual Concept

Research papers have addressed the KM-CRM interaction In Figure1, we are trying, also to picture the strong interaction widely, are getting interested in the KM-PLM interaction, but between SCM-CRM, SCM-PLM and PLM-CRM using double few papers pointed out explicitly the role KM-SCM bold arrows. This idea is consolidated by the work of Denis interaction. That is why we represent, KM closer to CRM Debeacker [Debeacker, 2005] who specifies these links. In fact first and PLM second. PLM and SCM systems are keen on developing the Supply In fact, the CRM domain is strongly related to KM, new Chain and the Design Chain. PLM and CRM systems are researches talk about —Customer Knowledge management“. interested in coordinating the Design Chain and the Demand In particular, customer knowledge and customer knowledge Chain. Finally SCM and CRM systems are working on a better management (CKM) have recently become a major focus of synchronisation of the Demand Chain and the Supply Chain. interest for companies who want to enhance their customer Below we further discuss the meaning of these links. relationship management (CRM) capabilities, obtaining and utilizing Customer-related knowledge is a prerequisite for 3.4.1 œ Interactions between Enterprise models: attaining CRM objectives [Mehtala et al, 2007]. Some of these six interactions are, already, well described in Knowledge capitalisation is an important issue on PLM, too, the literature (CRM-PLM, CRM-CM, PLM-SCM). But some as it is important for the company to know which knowledge others have to be more detailed and that is what we propose to to use for a PLM system, how to collect this knowledge and do in the following step of our research. how to update it when the company or the product evolves. First, the product lifecycle affect both the supply chain and the 3.4.3 œ Business models to complete the entgrated customers. The parts list determines the number of suppliers in enterprise model: the supply chain and their rows. The total lifecycle governs delivery deadlines to the customer. Chiang and To complete our integrated enterprise model, the business Trappey[Chiang and Trappey, 2007 ] and Sudarsan et al models that are applied in each case are signalled. Business [Sudarsan et al, 2005 ], for example, pointed out the role of models underline —the economic logic that explains how we PLM in enhancing SC and CR management. can deliver value to the customer at an appropriate cost“ Second, Customer knowledge is used in PLM and SCM [Joan, 2002]. There are three know industrial profiles: Make- models and decisions carried out in those two processes affect To-Stock, Build-To-Order and Configuration-To-Order the customer on form of product final form or deliveries times [Chiang et Trappey, 2007]. [Mehtala et al, 2007]. Debeacker [Debeacker, 2005] Make-To-Stock is applied in mass production industry with demonstrates the important challenges of PLM wich is to standardized products [Arnold & Chapman, 2004] such as synchronise the Design Chain (supported by PLM practices), process industry and some agro alimentary industry when the Supply Chain (supported by SCM practices) and the perish ability limits allow to make stocks. Make-To-Stock Demand Chain (supported by the CRM practices). industries are characterised by a sales forecast production Besides, Customer relationships affect both the product plans, little direct participation of the customer in the lifecycle and the company supply chain. [Parvatiyar and Sheth, production and the shortest delivery lead time [Dilworth, 2001]. Parvatiyar and Sheth continue by explaining that CRM J.B., 2000]. Under a Make-To-Stock production, companies involves the integration of marketing, sales, customer service, opt for using Supply Chain Management models, they allow and the supply-chain functions of the organization to achieve a better stock management give a great importance to greater efficiencies and effectiveness in delivering value.. delivery dead lines and allow continuous process flow [ Each company seeks to attend a high customer satisfaction Donlon, J.P, 1996]. level by adapting its product to the customer demands. Supply Build-To-Stock is commonly used for one-of-the-kind, Chains are organised or re-engineered according to the customised products [Arnold & Chapman, 2004]. Aerospace customer requests. Supply Chain Management models require Automotive ad Electromechanical industries are mainly customer‘s requirements as well as the specific company‘s following a Build-To-Stock production [Terzi, 2005]. processes and data to represent the global Supply Chain. SCM Build-To-Stock industries are using collaborative product research concludes that close customer relationship allows an designs (established with the customer), high customer organisation to differentiate its product from competitors, enrolment all along from design to delivery and relatively sustain customer loyalty and dramatically extend the value it long delivery lead times comparing to Make-To-Stock provides to its customers [Magretta, 1998]. [Arnold & Chapman, 2004]. PLM models are often used in a Build-To-Stock production 3.4.2 œ Knowledge as an integrating element: system. Chang and Trappey‘s study [Chiang et Trappey, Inside the triangle, the double arrows depict the interaction 2007] concluded that PLM components like —Requirements between KM and each one of the business process introduced management (RM), Bill of materials management (BMM) or earlier. Supplier relationship management (SRM)“ are highly used Knowledge is recognised as being —the key capital of under a Build-To-Stack business model. enterprises“ [Kalpic and Bernus, 2002] that contributes to Configuration-To-Order is between Make-To-Stock and enterprise competitiveness and provides the basis for long term Build-To-Order. This way of product design is more suitable growth, development and existence. KM could be seen as a for a mass production organised into two parts: a discipline integrating the other enterprise models: PLM, SCM manufacturing first part and a customised assembly second and CRM given that enterprise models are a formalisation of part [Chiang et Trappey, 2007]. Customer envolvment is enterprise knowledge [Kalpic and Bernus, 2002] relatively limited compared to the Build-To-Stock production but delivery lead times are reduced further [Arnold &

Paper Number -5- Copyright IDMME - Virtual Concept

Chapman, 2004]. Configuration-To-Order is offering In fact three important phases compose a product Lifecycle: customised products and personalized services. Relationship the Beginning Of Life (BOL), the Middle Of Life (MOL) with customer is, though, crucial for corporate enterprise and the End Of Life (EOL) [June et al, 2007], [Abramovici et survival [Wines L. 1996]. CRM are often used in this al, 2007] [Kritsis et al, 2003]. But for a better understanding configuration [Suhong Li et al, 2005]. of the product, the enterprise must have more details about Apart of these three business models, we have not found its lifecycle.Further PLM studies give a larger importance to papers showing a business model that fits the simultaneous the life cycle phases. June et al introduced design and application of SCM and PLM, SCM and CRM or CRM and production phases in the BOL of a product, maintenance, use PLM. and distribution in the MOL and finally remanufacturing and disposal in the EOL. After introducing different lifecycle models (such as GERAM Lifecycle model, STEP Lifecycle 4- Building a PLM Model: model,…), Terzi opted for a detailed lifecycle model too based on four major steps: product development, product 4.1 œ Luck of PLM Models: production, product use and product dismiss. Each one of these phases is then decomposed into different steps. Enterprise modelling techniques are proposing a set of models Chiang and Trappey, proposed a full detailed lifecycle view to enhance companies‘ performance in each one of these including requirement planning, conceptual design, domains. But managers need to understand these emerging manufacturing planning, manufacturing & test, maintenance models as quickly as possible, compare their theoretical and and disposal & recycling. practical validation and adapt them to their companies‘ In our PLM model we propose to give further details about specifications. We aim at providing the managers with a each lifecycle phase ranged into BOL, MOL and EOL modelling technique allowing them to understand the previous phases. Each phase is held into a box that shows, at a first enterprise models characteristics and decide to apply the level, the number of staff working on it and, at the second models aligned with their strategic objectives. level, the main results obtained. SCM is proposing different models to depict a supply chain. A BOL includes concept development, Product design, simple flow diagram is meant to depict the important Prototyping& testing, process planning, supply chain components of a supply chain and the flows exchanged planning and production. The transition between these first between them. Part of the —lean manufacturing tools“, the phases of the lifecycle consists of information flows mainly Value Stream Mapping model is supposed to give a broader (black arrows in the diagram) such as: product design view of the supply chain of a company and offers alternative specifications, prototype test results, design changes, Bill Of tools to make physical and information flows run easier and to materials Details… reduce wastes in the supply chain. MOL includes delivery& installation and maintenance& CRM models are based on diagrams defining the context of the other services to the customer. Material and product flows study and the possible actors in interaction then hypothesis are (Blue bold arrows) are added to the flows exchanged made concerning the possible relations or interactions between between different stages. those actors when managing the customer relationship. Finally Finally EOL includes removal& disposal and recycling. The interviews and case studies confirm or reformulate the initial information & material flows are exchanged between these hypothesis to obtain a model linking different actors in a phases. Besides, recycled materials and product parts for customer relationship context. reuse are, ideally, turned back to the first stage of the product As a recent issue in the literature, we could find few models of lifecycle. Interoperability and traceability are the main issues PLM most of which depends strongly on the particular case to consider when building a PLM model [Terzi, 2005], [Terzi studied and can not be used with other companies. We try to et al., 2006]. To keep track of the product and its evolution build a general PLM model supporting PLM principles and through the lifecycle phases we opted for settling down a allowing managers to apply a PLM strategic vision of their unique data base. It holds the information and the knowledge company. from all lifecycle phases. Including a knowledge base in the PLM model, helps 4.2 œSteps to build a PLM model: knowledge management activities: knowledge capitalisation, The PLM model proposed in this article is meant to enhance knowledge sharing and knowledge creation. These activities the comprehension of the PLM vision. It is based on the are said as part of the PLM vision [Stark, 2005]. previous research results and a literature review among the papers dealing with PLM. Our model is based on a semi- formal language, pictograms and symbols are organised to according to the most important PLM principles. The PLM model must keep track of the Lifecycle phases of the product depicted. As pointed out by Stark [Stark, 2005], PLM is —the activity of managing a product across its lifecycle, from cradle to grave, from the very first idea for the product all the way through until it is retired and disposed of“. It is important for the company to have full details about the lifecycle. PLM existing models give a view of the lifecycle phases but the degree of details differs.

Paper Number -6- Copyright IDMME - Virtual Concept

Concept development Production Delivery/ Installation Removal/ Disposal

Number of people Number of people Number of people Number of people

Product concept Procurement Supply Chain Conditions of Part Manufacturing Management retirement Assembly remanufacturing

Product, material flow Product Design Supply Chain Maintenance/ Service Recycling Reverse Product, material Planning flow from EOL to BOL: Parts Number of people Number of people Number of people Number of people components reuse, Material reuse… Design specification Mode of use Material recycle Information flow Suppliers network failure Parts reuse planning Maintenance process Information exchange: Customer network •BOL-MOL: Up-to-date product planning information, Product usage info (failure, Prototyping / Testing Process planning maintenance…), Customer special requirement… Middle Of Life End Of Life •MOL- EOL: Product status, Number of people Number of people Product history information Information Data Recovery information Test results Core product model Base •BOL-EOL: Mode of use, Design changes Assembly Model Material information for reuse Bill Of Material details Knowledge Data Conditions of retirement and Base disposal, Recovery information, Assembly/ disassembly Information Product Data Beginning Of Life Base

Figure 2 : A proposition of a PLM model

Paper Number -7- Copyright IDMME - Virtual Concept

- Exhaustiveness [Walliser, 1977]: To avoid being misunderstood, we prefer to use genericity, as this 5- Discussion and research perspectives: characteristic is not meant to have a model that depicts all of the possible cases but it underlines Building a PLM model is essential to complete our the ability of the model to depict at least more integrated enterprise vision. But we have not addressed yet than a single system. It is not, hence, built the validation of the proposed model. This issue will be specifically to an enterprise system. part of our future researches as the study of enterprise Pragmatic characteristics are mainly related to the models includes a focus on the validation technique. understanding of the model by its interpreter. They consist As part of our integrated enterprise vision, we began by of: studying the validation techniques used with SCM and - —Sensibility“ [Walliser, 1977]: the model has to CRM models. be precise enough to report different cases in Many SCM models are validated by case studies different models. If the studied enterprise changes [Abdulmalek & Jayant. 2007.] proposed a Value Stream the model should be —sensible“ enough to report Mapping model through the Supply Chain of steel this change to its user. manufacturing company. The results of their model were - —Suppleness“ [Walliser, 1977]: As the systems validated by the improvements obtained when using the described are under constant change, the model model in the company. has to be easy to change and offering re Avlonitis and Panagopoulos [Avlonitis et al, 2005] engineering qualities to accompany an enterprise proposed a CRM model for implementation of CRM through its evolution. technology and its impact on sales performance. All By proving that a model has these different hypotheses were tested on a case study including characteristics, we validate the structure of the model. We pharmaceutical firms and using interviews. will have to validate, then, its use through the validation of The validation methodology proposed will not, only, be its different function. used on the PLM model proposed in this article. The After studying various types of scientific models (dealing objective of our research is to try to prove the validation of with different systems also), Walliser [Walliser, 1977] SCM models, CRM models and KM models. Managers are identified different functions for a model: normative facing too many enterprise models and must choose function, decision- making fucntion, cognitive function… between them the most effective one. Providing them with As we are orienting our work to help management decision a theoretical and practical validation method could help making, we have to prove that the SCM models, CRM them choose the pertinent model. models and finally the PLM model build are having three Based on the work of Bernard Walliser [Walliser, 1977], specific functions: the decision- making function, the each model holds a set of characteristics. The cognitive function and the descriptive function. characteristics of a model are syntactic, semantic and - The decision making function is consists of pragmatic. The modern usage of these terms was attributed —fixing control variables to reach the needed to Charles Morris (1938), who first distinguished three output variables taking into account the evolution braches of inquiry in language studies: syntactic, semantic of external variables“ [Bernard Walliser. and pragmatic. Systèmes et modèles, Introduction critique à Syntactic characteristics are related to the grammar used to l‘analyse de systèmes, ]. An enterprise model is build the model and the specific primitives of the semi meant to facilitate decision making. formal language used. They include: - The cognitive function emphases the role of - Clear grammar structure: Being able to write knowledge into enterprise modelling. The model down the model‘s grammar is a way of proving has to facilitate the understanding of the system the coherence of the model and its robustness. and knowledge acquisition, it —depicts internal And the robustness of the model relationship between input and output variables“. - Saturation [Bernard Walliser. Systèmes et [Walliser, 1977] modèles, Introduction critique à l‘analyse de - The descriptive function or the representational systèmes, ]: the set of primitives offered to build function completes the cognitive function. Before the model are sufficient to depict enterprise depicting the relationship between different systems studied, that is to say there is no variables the model has to define the type and role redundant primitives that can be deduced from of all variables used, it has to depict accurately another one. The model displays pertinent the system to allow a good understanding of its primitives which use is clear and know to user (in functioning and uses. our case enterprise management staff) Besides these three common functions each enterprise Semantic characteristics are related to the way the model is model proposed has specific functions related to the understood it includes the fact that the model have to be: domain it is used in: SCM, CRM or PLM. After - Simple [Walliser, 1977] : —the number of determining these different functions through a literature hypothesis or steps made into the model have to review and case studies in practice, we will run a be as simple and reduced as possible“ [Walliser, functional analysis for each discipline to validate the large 1977]. This characteristic is extracted from the set of function of each model studied and though validate —parsimony‘s principle“ of Okham [Alféri, 1989.] the model.

Paper Number -8- Copyright IDMME - Virtual Concept

6- Conclusion: So we tried to propose a PLM model based on a wide literature review and search for PLM models. We Enterprise modelling is proposing a variety of tools that identified the components of a PLM vision and translate addresses different enterprise aspects: the functional these components into a semi formal language using aspects, the data/information aspect and the resources redundant primitives in PLM models found in the aspect. literature. Process coordination could be a good way to have an Models validation is an important question that we are integrated view of these aspects. We focused though on aiming to answer to in the next step of our research. Not three core business processes: SCM, CRM and PLM. only, have we to prove the validation of our proposed Because of their knowledge characteristics, we added KM PLM model but we should, also, build a validation models to our proposed integrated enterprise model. methodology to evaluate SCM, CRM, PLM and KM But when getting to study closely enterprise models under models and helps decision making to choose the most this specific vision, we come to notice that PLM models suitable model to apply in an enterprise. are scarce, compared to SCM and CRM models, and do not contain all the PLM concepts. Most of these models are adapted especially to specific enterprises and are, though, difficult to re produce in other cases.

[GS] Global Supply Chain Forum (GSCF): ou connue avent pour le —Research Roundtable of the International 7- References Center for Competitive Excellence, de l‘Université de la Floride du nord [A] Alféri Pierre. Guillaume d‘Ockham le singulier. Les [II] IIT Force. GERAM: Generalised Entreprise Reference Editions de Minuit, 1989. Architecture and Methodology. 1999 [AC] Arnold, J.R.T., Chapman, S.N., 2004. Introduction to [JK] Jun Hong-Bae, Kiritsis Dimitris, Xirouchakis Paul. Materials Management. Pearson Prentice Hall, New Jersey Research Issues on closed loop PLM. Computers in [AP] Avlonitis George J., Panagopoulos Nikolaos G.. Industry 58 (2007) 855œ868 Antecedents and consequences of CRM technology [KB1] Kalpic Brane, Bernus Peter. Business process acceptance in the sales force. Industrial Marketing modelling in industry- the powerful tool in enterprise Management 34 (2005) 355œ 368 management. Computers in Industry 47, 299-318, 2002. [AR] Abdulmalek Fawaz, Rajgopal Jayant. Analyzing the [KB2] Kiritsis Dimitris, Bufardi Ahmed, Xirouchakis benefits of lean manufacturing and value stream mapping Paul. Research issues on product lifecycle management via simulation : A process sector case study. International and information tracking using smart embedded systems. Journal of production economics, n° 107, 2007. Advanced Engineering Informatics 17 (2003) 189œ202 [AS] Abramovici, Michael and Sieg Olaf C. Status and [KV] Kosanke K., Vernadat F., Zelm M.. CIMOSA: development trends of Product Lifecycle Management. enterprise engineering and integration, Computers in Product Data Management, Product Lifecycle Industry 40 1999.83œ97 Management,Product development, Digital Engineering, [LC] Lambert Douglas M, Cooper Martha C. Issues in Engineering Collaboration Supply Chain Management. Industrial Marketing [BE] Boughzala Imed & Ermine Jean- Louis. Management Management 29, 2000 des connaissances en entreprise. Lavoisier , 2007 [L] Liebowitz Jay. Knowledge Management Handbook. [CT] Chiang Tzu-An, Trappey Amy J.C. Development of CRC Press 1999 value chain collaborative model for product lifecycle [M1] Macintosh Ann, Artificial Intelligence Applications management and its LCD industry adoption. Int. J. Institute, University of Edinburgh Production Economics 109 (2007) 90œ104 [M2] Magretta, J. The power of virtual integration: an [D1] Debeacker Denis. Product Lifecycle Management. interview with Dell computers‘ Michael Dell. Harvard 2002 Business Review 76, 72-84. 1998 [D2] De Marco T. Structured analysis and system [M3] Magretta Joan. Why Business models matter? specification. ACM Classic Books Series Classics in Harvard Business Review, 2002 software engineering 1979 [M4] Melan EH. Process management. A systematic [D3] Dilworth, J.B., 2000. Operations Management. Experience. Springer 1993 Dryden Press, Orlando [MM] Menzel Christopher & Mayer Richard J The IDEF [D4] Donlon, J.P, Maximising value in the supply chain. family of languages.. University of Texas. www.idef.com Chief Executive 117, 54-63, 1996 [MS] Mehtälä Mari, Still Johanna. A Cross-Functional [DV] Doumeingts G., Vallespir B., Chen D. GRAI grid, Process Framework for Customer Knowledge decisional modelling, in: P. Bernus, K. Mertins, G. Management. University of Oulu, Department of Schmith (Eds.), Handbook on Architecture of Information Marketing System International Handbook on Information Systems, [PS] Parvatiyar, A., & Sheth, J. N. (2001). Customer Springer, Berlin, 1998. relationship management: Emerging practice, process, and [E] Eymery Pascal. La stratégie Logistique. Que sais-je, discipline. Journal of Economic and Social Research, 3(2), 2003 1Þ34

Paper Number -9- Copyright IDMME - Virtual Concept

[R] Ross D.T. "Structured Analysis (SA): A Language for Communicating Ideas," IEEE Transactions on Software Engineering, vol. 3, no. 1, pp. 16-34, Jan/Feb, 1977 [RR] Rigby, D. K., Reichheld, F. F., & Schefter, P. (2002). Avoid the four perils of CRM. Harvard Business Review, 80(2), 101Þ109. [S] Stark, John. Product Lifecycle Management. 2006. [SF] Sudarsan R. , Fenves S.J.,. Sriram R.D, Wang F. A product information modeling framework for product lifecycle management. Manufacturing Systems Integration Division. Computer-Aided Design 37 (2005) 1399œ1411 [SS1] Srivastava, R.K., Shervani, T.A. & Fahey, L. Marketing, business processes, and shareholder value: an organizationally embedded view of marketing activities and the discipline of marketing. Journal of Marketing, 63(Special Issue 1999), 168Þ179 [SS2] Suhong Li, Subba Rao, Ragu-Nathan T.S, Bhanu Ragu-Nathan. Development and validation of a measurement instrument for studying supply chain management practices. Journal of Operations Management 23, 618-641, 2005 [T1] Terzi Sergio. Doctoral dissertation : Elements of Product Lifecycle Management: Definitions, Open Issues and Reference Models. Public discussion on 27 May 2005 [T2] Terzi Sergio, Cassina Jacopo, Panetto Hervé .Development of a Metamodel to Foster Interoperability along the Product Lifecycle Traceability, in Interoperability in Enterprise soft wares and applications, Springer London 2006 [V1] Vernadat François. Entreprise modelling and integration: principles and application, Chapman & Hall, London, 1996, [V2] Vernadat François. Techniques de modélisations en entreprise : Applications aux processus opérationnels. 1999 [W] Wines L. High order strategy for manufacturing. The Journal Of Business Strategy, 17 (4), 1996 [Z] Zablah, A.R., Bellenger, D.N. & Johnston, W.J. (2004). An evaluation of divergent perspectives on customer relationship management: Towards a common understanding of an emerging phenomenon. Industrial Marketing Management, 33(6), 475Þ489.